smq/directoryAn evolving quant resource archive
Back to directoryResource
Paper / 2019SMQ / 166729409630681
Volatility uncertainty quantification in a stochastic control problem applied to energy
Emmanuel Gobet / Francisco Bernal / Jacques Printems
numerical methods / partial differential equationsResource overview

Volatility uncertainty quantification in a stochastic control problem applied to energy

Paper2019

by Emmanuel Gobet, Francisco Bernal, Jacques Printems

Tags
numerical methodspartial differential equations

Access resource

Open original source Understand this paper

Continue on SelfMadeQuant

Understand this paper

Suggested foundations for volatility models and surfaces and optimisation and numerical methods. Specialist prerequisites vary by paper.

Before you read

  1. Stochastic Processes, Brownian Motion and Itô's Lemma

    Follow diffusion-based models and their assumptions.

  2. ARCH and GARCH

    Separate conditional volatility from observed returns.

  3. Vectors, Matrices and Linear Systems

    Read the linear algebra used to define a numerical problem.

  4. Constrained and Convex Optimisation

    Identify the objective, constraints and conditions for an optimum.

Go further

  1. Stochastic Volatility and the Heston Model

    Study a correlated stochastic-variance model.

  2. Reading the Implied Vol Surface — Moneyness, Term Structure, and Quoting Conventions

    Interpret prices across strikes and expiries.

  3. Calibration as an Inverse Problem

    Understand identifiability and fitted model parameters.

Explore a related reading path

Lesson links open public previews. Access to full lessons depends on the topic and your membership.

Explore Advanced Derivatives and Exotic Options Explore Linear Algebra, Optimisation and Numerical Methods

Keep exploring

Related resources

More ideas from similar topics.

6

From the same author

Emmanuel Gobet, Francisco Bernal, Jacques Printems

6